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pro vyhledávání: '"A. Bhateja"'
In machine learning, metric elicitation refers to the selection of performance metrics that best reflect an individual's implicit preferences for a given application. Currently, metric elicitation methods only consider metrics that depend on the accu
Externí odkaz:
http://arxiv.org/abs/2501.00696
We investigate granular flows over an inclined rigid base, which is vibrated externally in a direction normal to itself, through discrete element simulations. We vary the base inclination angle theta, vibration frequency f, and amplitude A to study c
Externí odkaz:
http://arxiv.org/abs/2411.06093
Increasingly large imitation learning datasets are being collected with the goal of training foundation models for robotics. However, despite the fact that data selection has been of utmost importance in vision and natural language processing, little
Externí odkaz:
http://arxiv.org/abs/2408.14037
Autor:
Bhateja, Chethan, Guo, Derek, Ghosh, Dibya, Singh, Anikait, Tomar, Manan, Vuong, Quan, Chebotar, Yevgen, Levine, Sergey, Kumar, Aviral
Pre-training on Internet data has proven to be a key ingredient for broad generalization in many modern ML systems. What would it take to enable such capabilities in robotic reinforcement learning (RL)? Offline RL methods, which learn from datasets o
Externí odkaz:
http://arxiv.org/abs/2309.13041
Publikováno v:
Journal of Physics: Conference Series 2023
During the COVID-19 pandemic, medical imaging techniques like computed tomography (CT) scans have demonstrated effectiveness in combating the rapid spread of the virus. Therefore, it is crucial to conduct research on computerized models for the detec
Externí odkaz:
http://arxiv.org/abs/2309.12638
Passive observational data, such as human videos, is abundant and rich in information, yet remains largely untapped by current RL methods. Perhaps surprisingly, we show that passive data, despite not having reward or action labels, can still be used
Externí odkaz:
http://arxiv.org/abs/2304.04782
Autor:
Rituraj Upadhyay, Aastha Dhakal, Caroline Wheeler, Rebecca Hoyd, Malvenderjit Jagjit Singh, Vidhya Karivedu, Priyanka Bhateja, Marcelo Bonomi, Sasha Valentin, Mauricio E. Gamez, David J. Konieczkowski, Sujith Baliga, John C. Grecula, Dukagjin M. Blakaj, Emile Gogineni, Darrion L. Mitchell, Nicholas C. Denko, Daniel Spakowicz, Sachin R. Jhawar
Publikováno v:
Cancer Biology & Therapy, Vol 25, Iss 1 (2024)
Head and Neck Squamous Cell Carcinoma (HNSCC) comprises a diverse group of tumors with variable treatment response and prognosis. The tumor microenvironment (TME), which includes microbiome and immune cells, can impact outcomes. Here, we sought to re
Externí odkaz:
https://doaj.org/article/9cd2a6b3a01a4b8fbe8b5d225ed3cc93
We investigate axial segregation of binary mixtures in a laterally shaken horizontal channel formed by ratchet-like sidewalls that appear as concatenated trapeziums when not offset axially. Grain mixtures shaken in such a channel are observed to segr
Externí odkaz:
http://arxiv.org/abs/2210.08040
Autor:
Kumari, Pooja, Bhateja, Bhumika
Publikováno v:
South Asian Journal of Business Studies, 2022, Vol. 13, Issue 1, pp. 118-136.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/SAJBS-05-2021-0185
Autor:
Bhateja, Ashish, Jain, Sahaj
We examine the gravity-induced flow of dry and cohesionless granular media through an outlet placed eccentrically in a planar silo, employing computations based on a soft-sphere discrete element method. The vertical velocity profiles, measured at the
Externí odkaz:
http://arxiv.org/abs/2112.14129